Engineering Program Manager

The application window is expected to close on: 08/24/2026

Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.

You will join a team building complex, cloud-native SaaS and AI-powered products that move from concept through production launch, adoption, and ongoing operation. The team works across product management, engineering, applied AI/ML, data, infrastructure, security, compliance, customer experience, and go-to-market partners to deliver customer-ready capabilities s is a highly multi-functional environment where transparency, execution, rigor, and strong partnership are critical to success.

The work is fast-moving, and focused on delivering enterprise-grade products and AI capabilities that are reliable, secure, and built for real-world adoption.

As a Technical Program Manager, you will lead sophisticated SaaS and AI-powered product initiatives from strategy through production delivery and operation. You will bring structure to ambiguous programs and drive alignment across large, multi-functional teams.

• Turn product and technical strategy into clear plans, milestones, dependencies, success metrics, and ownership across teams.

• Lead large programs with moderate to high risk, multiple interdependencies, and impact across customers, partners, platforms, and releases.

• Lead programs spanning product, engineering, design, data, applied AI/ML, infrastructure, security, compliance, customer experience, and go-to-market teams.

• Influence product and technical roadmaps by managing critical paths, sequencing, architecture dependencies, delivery tradeoffs, risks, resources, and commitments.

• Lead agentic AI programs from definition through production and iteration, coordinating agent workflows, model and tool integration, grounding, evaluations, guardrails, observability, and human oversight.

• Establish evaluation-driven delivery practices so AI quality, safety, latency, cost, and reliability are measured before launch and monitored in production.

• Partner with engineering and quality teams to define validation, release, observability, and operational-readiness requirements for continuous integration and deployment.

• Communicate program status, technical tradeoffs, risks, and decisions to executive audiences with clear recommendations.

• Provide guidance and mentorship to other program managers and team members while driving a strategic horizon of one year or more.

• Bachelor’s degree with 8+ years of related experience, Master’s degree with 6+ years of related experience, or PhD with 3+ years of related experience.

• Experience leading complex technical programs for enterprise SaaS products through production launch and ongoing operation.

• Experience directly leading at least one generative AI, LLM-based, or agentic capability through development, production launch, and post-launch iteration.

• Previous experience leading cross-functional technical programs through influence in a highly matrixed organization.

• Experience in cloud platforms, APIs, distributed systems, data systems, and modern AI development and deployment practices.

• Experience leading multi-team SaaS or AI programs involving cloud-native architecture, API integrations, data platforms, AI evaluations, security, reliability, and customer-facing production launches.

• Experience with generative AI and agentic systems, including agent orchestration, tool use, retrieval-augmented generation, evaluation frameworks, guardrails, observability, and human-in-the-loop workflows.

• Ability to understand system architecture, identify cross-platform dependencies, facilitate engineering tradeoffs, and translate complex technical risks and decisions for executive audiences.

• Experience applying fit-for-purpose development and execution practices, including Agile methodologies, to improve planning, decision-making, delivery, and learning.

• Strong ability to bring structure to ambiguous initiatives, drive timely decisions, and create accountability across product, engineering, security, compliance, customer experience, and go-to-market stakeholders.